Address of the bookmark: https://phytozome.jgi.doe.gov/pz/portal.html

https://www.nasa.gov/reference/osdr-data-processing/

Address of the bookmark: https://www.nasa.gov/osdr/

• January 20th, 2016 - New! Bpipe 0.9.9 released!
• Download latest, all
• Documentation
• Mailing List (Google Group)

Bpipe has been published in Bioinformatics! If you use Bpipe, please cite:

Sadedin S, Pope B & Oshlack A, Bpipe: A Tool for Running and Managing Bioinformatics Pipelines, Bioinformatics

Address of the bookmark: http://docs.bpipe.org/

More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&c=leidosbiomed&id=2040

Understanding Large Language Models

LLMs are AI systems trained on extensive datasets of natural language. Their ability to model context, identify patterns, and generate coherent language has proven invaluable across domains, including bioinformatics. By fine-tuning these models on biological datasets, researchers can unlock insights into molecular biology, systems biology, and beyond.

Key Applications of LLMs in Bioinformatics

1. Annotating Biological Data

Annotating genomic and proteomic data is fundamental yet labor-intensive. LLMs streamline this process by extracting functional annotations from literature and databases, predicting gene and protein functions, and providing automated insights.

2. Mining Scientific Literature

The exponential growth of publications presents a challenge for researchers to stay updated. LLMs can process large volumes of text to extract key findings, summarize papers, and identify trends, thereby facilitating efficient literature reviews.

3. Predicting Gene and Protein Functions

By leveraging sequence data and annotations, LLMs can predict the functions of uncharacterized genes and proteins. This capability is particularly useful for studying non-model organisms and orphan genes.

4. Drug Discovery and Repurposing

LLMs enable pattern recognition across chemical, genomic, and clinical datasets, identifying novel drug candidates and repurposing existing drugs for new therapeutic targets. They can simulate interactions between drugs and biological molecules, accelerating the discovery pipeline.

5. Generating Hypotheses for Research

LLMs analyze complex datasets to propose testable hypotheses. For example, they can predict protein-protein interactions, identify regulatory motifs, or model evolutionary processes in genomes.

Advantages of LLMs in Bioinformatics

• Scalability: LLMs process massive datasets rapidly, reducing the time required for data analysis.

• Versatility: These models adapt to diverse bioinformatics tasks, from genomic annotation to network analysis.

• Contextual Insights: By synthesizing information across disparate datasets, LLMs provide integrative insights into biological systems.

Challenges in Applying LLMs

Despite their promise, LLMs face limitations:

• Data Quality and Bias: Inaccurate or biased datasets can affect model predictions, necessitating rigorous data curation.

• Interpretability: Understanding the decision-making process of LLMs remains a critical challenge, especially in high-stakes fields like genomics and medicine.

• Resource Intensity: Training and deploying LLMs require substantial computational power, which can limit accessibility.

• Ethical Concerns: Handling sensitive genomic data raises privacy and security issues, emphasizing the need for ethical guidelines.

Future Prospects

The continued development of LLMs tailored for bioinformatics promises exciting advancements. Specialized models trained on omics data, open-access platforms, and interdisciplinary collaborations will expand the utility of LLMs. Moreover, integrating LLMs with other AI technologies, such as graph neural networks and reinforcement learning, can unlock deeper biological insights.

Conclusion

Large language models are revolutionizing bioinformatics by addressing longstanding challenges in data annotation, literature mining, and function prediction. Their ability to analyze complex biological datasets efficiently positions them as indispensable tools for modern research. As bioinformatics embraces AI, the synergy between LLMs and biological sciences holds the potential to unravel the complexities of life with unprecedented precision and scale.

Read more: https://edu.t-bio.info/amity-university-summer-bioinformatics-program-registrations-are-open/

More at http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369

Address of the bookmark: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369

More at https://boards.greenhouse.io/twistbioscience/jobs/3135495?gh_src=9ecc0b941us

Address of the bookmark: https://biokit.readthedocs.io/en/latest/index.html

About Fellowship:
CSIR Nehru Science Postdoctoral Research Fellowship Scheme is an Research Fellowship awarded/given by HRD Ministry, Govt. of India every year to more than 100 fellows.

It was started to identify promising and young researchers with novel ideas and provide them research opportunities in the areas of basic science, engineering, medicine & agriculture.

The fellowship aims at facilitating their transition from mentored to independent research career.

In addition, check these ICTS Research Fellowships:
1.) Max-Planck Partner Group Fellowships 2017-18
2.) ICTS-Simons Postdoctoral Fellowships 2017
3.) ICTS Post Doctoral Fellowships 2017
4.) Airbus Prize Postdoctoral Fellowship 2017-18

Eligibility: To be eligible for this fellowship, you:
1.) PhD degree (within 3 years of award of PhD degree), OR
2.) Those who have submitted PhD theses.
3.) Applicants should have research publications in good impact factor SCI journals.
4.) Indian nationals, Persons of Indian Origin (PIO) & Overseas Citizen of India (OCI), a can also apply.
5.) Maximum Age Limit: 32 years.

Duration:
– 2 Years.
– extendable for a maximum of 1 more year based on performance.

Remuneration:
– Rs. 50,000/- per month plus House Rent Allowance (HRA)
– A contingency grant of Rs. 3.0 lakh per annum.
– 25% of the contingency grant can be used for domestic and international travel.

Mode of Selection: You can apply throughout the year, but selection will be made twice a year, in June and December.

How to Apply:
– Read the instructions, given at Annexure-I in this PDF file.
– And, application form is given as, Annexure-II.
– Fill the form & send it to the given address in the PDF file.

Deadline: Rolling Deadline (Applications accepted throughout the year)

Also See: Research Internship/ Fellowship in India:
1.) IIT Bombay Research Internship Awards Programme 2016-17
2.) IIT Delhi Internship Program 2016-17
3.) DAAD WISE – International Internship in Germany
4.) Summer Research Fellowship Programme| JNCASR Bangalore
5.) Indian Academy of Sciences Summer Internships 2017
6.) Winter Internship – IIT Bombay NPDE-TCA
7.) Viterbi – India Program 2017 | Research Internship in US
8.) Internship – Centre for Stem Cell Research, Vellore

Accommodation & other benefits:
– Accommodation may be provided by CSIR, if available.
– Medical benefits as per CSIR norms.

For more details:
– Check this PDF Notification of Fellowship.
– List of CSIR Labs & their work/activities can be seen at www.csir.res.in.